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This video is part of the Udacity course “Machine Learning for Trading”. Watch the full course at https://www.udacity.com/course/ud501
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Bootstrap aggregating bagging
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This video is part of the Udacity course “Machine Learning for Trading”. Watch the full course at https://www.udacity.com/course/ud501
Original source
24 responses to “Bootstrap aggregating bagging”
Way of explanation superb..
Easy to understand..
excellent explanation – many thanks, sir
really precise and easy understanding explanation, thank you, sir! really save my life 🙂
Weird my school teaches n' should be the same size as n. Anyways it doesn't change that much i guess
those bags look like slug aliens from mars. also i sneezed while watching this which proves illuminati did 9/11
This is the best explanations on bagging I've ever seen. Many thanks 👍🙌👌
What algorithm is used in the model step. Is this applicable for any algorithm?
Great video. I have two questions. Since the data can be the same in the same subset it can also be exactly the same (although the chance is low ofc) on another subset right? In the case of random forests, since features are also selected randomly from the dataset, can they also be the same in different decision trees? Thanks in advance.
banging
thank you so much 🙂
Could someone please explain to me what he meant by "you can simply wrap this up in an API"? How to do that and how does it help?
extremely clear
well explained, thank you very much
Thanks a lot!
very well done…. gr8
Wow – great explanations on concepts most other people take 30 mins to explain with half the effect. Subscribed!
so we use single algo for all different bags? or different learners for different bags ?
Nice explanation
Hi what tablet is it? Is it wacom? Will that be very expensive??
only person who explained this properly imo
Where does the unknown X come from?
Well explained.
Very concise explanation – thanks for posting this!!
In every video, what you explain is fine but is not enough to explain the topic of your header